### Introduction to distribution plots

Introduction to distribution plots
Distribution plots are the only widely used graphics that display the shape of an entire probability distribution. As such, they contain more information than simpler graphics like box plots or interval plots. For this reason, distribution plots must be based on large datasets; typical uses include showing the range of values of a measurement taken in a large group of patients or summarising the thousands of iterations produced by probabilistic simulation models.
Although these diagrams may be appealing to specialist audiences, they may be less helpful for those without the necessary technical background. Distribution plots can be useful when making comparisons between treatments or groups as they convey a sense of statistical significance.

Distribution plots can be generated in many software packages including Stata, R, SAS, SPSS, Tableau, Spotfire, QlikView, IBM Many Eyes, Microsoft Excel®, and Google Drive. Dynamic and interactive distribution plots could overcome some of the limitations faced when presenting static plots since better functionalities and guidance can be built into the graphics to aid understanding.